AI Software Intern (Canada)

Tenstorrent University Jobs; Toronto; On-site; CAD 110,000 - 165,000; Full time

Job summary

Tenstorrent is seeking motivated students and early career researchers to contribute to a range of teams (Kernels, Models, Inference, Runtime, Scale Out, Compiler & Infra) in a Toronto on-site role. You will work on high-performance kernels, ML model optimization, and production ML serving infrastructure, collaborating across disciplines to push hardware-software co-design.

The position targets BS/MS/PhD candidates in CS/CE/Physics/Math with exposure to parallel processing, ML, or distributed

Qualifications

• Pursuing BS/MS/PhD in CS/CE/Physics or related field.
• Experience with model quantization, kernel fusion, or other optimization techniques.
• Hands-on experience deploying models with PyTorch for inference or training.
• Knowledge of RTL/HDL is a plus.

Responsibilities

• Develop high-performance kernels on Tenstorrent hardware.
• Optimize ML models (LLMs, vision models) for our hardware.
• Develop inference server software and optimizations.
• Build the runtime that manages memory, scheduling, and code execution.

Skills

Model quantization

Kernel fusion

High-performance programming

PyTorch

CUDA

Python

TensorFlow

JAX

RTL/HDL

Education

BS/MS/PhD in CS/CE/Physics/Math

Job description

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.

Overview: This is the team that makes "it runs on Tenstorrent hardware" actually true for real models, at real scale, and builds the infrastructure that keeps the rest of engineering moving fast.

Location: This role is on-site in Toronto, ON.

What you might work on: This posting spans multiple teams within Kernels, Models, Inference, Scaleout & our Runtime teams. One application, one recruiter screen, then we match you to the specific team and location that fits best. Teams include:

• Kernels: Develops high performance kernels on Tenstorrent hardware
• Models: Optimizes ML models (LLMs, vision models, video and image generation, and other architectures) for our hardware
• Inference Server: development and serving-side optimization
• Runtime: Builds the software engine that manages memory, task scheduling, and code execution on hardware while an application is actively running.
• Scale Out: communication and coordination between devices in a distributed AI system.
• Compiler & Infra: Create tools that optimize AI models into high-performance programs on Tenstorrent hardware, covering memory planning, profiling, debug, and emulation.

Who You Are

• Currently pursuing a BS, MS, or PhD in Comp Sci, Comp Eng, Physics/Math or a related field.
• Coursework or projects any of the following: parallel processing, machine learning or distributed systems.
• A high comfort level as an end user of AI and agentic flows.

What We Need

• Experience with model quantization, kernel fusion, or other optimization techniques; or low level high performance programming.
• Hands on experience working with Pytorch, experimenting with and deploying models, for inference or training.
• Experience with C/C++ or kernel development in languages like CUDA, or Python and at least one ML framework (PyTorch, TensorFlow, JAX).
• Knowledge of RTL, HDL is nice to have on certain teams.

What You Will Learn

• How models get adapted to run well on specialized hardware
• How to write high performance code that can get the most out of the underlying hardware
• Production ML serving infrastructure at scale
• How infrastructure choices affect the velocity of an entire engineering org

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.